Influence of sensorimotor training in the integration of sensory information in an overweight situation
Bibliographic record
Abstract
Le poids d’un équipement comme ceux des militaires entraîne une instabilité posturale entraînant fatigue musculaire et risque de chute. Le but de cette thèse a été d’étudier les bases neurales de cette instabilité et de déterminer un entraînement permettant de la réduire. Nous avons donc équipé des participants non-athlètes et des judokas (connus pour leur excellente aptitude en termes d’équilibre et de gestion de la masse de l’adversaire) avec une veste de 20kg et avons étudié la transmission des informations provenant de la sole plantaire lors du maintien de la position debout. De manière surprenante, les résultats ont montré une diminution de la quantité d’information provenant des pieds chez les non-athlètes lors de la charge (ce qui expliquerait leur instabilité), diminution absente chez les judokas grâce à des modifications comportementales leur permettant de conserver leur stabilité face à la charge. Ainsi, cet entraînement permettrait de prévenir les risques liés à la gestion d’un surpoids.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".